1. Field of the Invention
Embodiments of the present invention may relate to surveillance systems. Specifically, various embodiments of the invention may relate to a video-based intelligent surveillance system that can automatically provide real-time situation awareness regarding the scene under monitoring.
2. Related Art
Some state of art intelligent video surveillance (IVS) systems can perform content analysis on the frames taken by surveillance cameras. Based on user-defined rules or policies, such IVS systems can automatically detect potential threats by detecting, tracking and analyzing the targets in the scene. The performance of such IVS systems is thus highly correlated with the performance of target tracking. There are many factors that may impact the performance of target tracking, among which the most commonly seen ones are target occlusions and stationary target tracking.
When the target is moving by itself and the whole body of the target can be seen, the tracking process is usually simple and straightforward. But when the target is occluded or partially occluded by other targets or by static background objects, or when the target is occluding other targets, the tracker may become confused, which may cause lost tracking or target false tracking. A conventional method to handle occlusion is to use prediction, where the location of an occluded target is provided by predicting its location based on previous non-occluded locations. This method, however, usually works only when the occlusion duration is short and the target has consistent velocity before and during occlusion.
Another problematic scenario for a conventional target tracker is the tracking of non-moving targets, denoted “stationary targets.” A stationary target refers to a target that is different from a current background scene, but which is not moving. A stationary target may correspond to one of two types of targets: one is a stopped moving target, and the other is the ghost of a target after the target has moved away from the original background. Conventional target trackers usually handle such stationary targets by burning them into background and by forgetting them after tracking them for some significant time duration. This scheme, however, assumes that the stationary target detected will not move again, which is not true in many real applications. In addition, since the tracker may lose the target once it has been burned into background, this scheme usually requires a significant consistently stationary time period prior to burning into background, during which the target may cause some occlusions with other moving targets, which may further complicate the scenario.